[A] The list of replication files:
1. Code_Paper
2. Code_Appendix

[B] Data dictionary: Please refer to Section IV.A Regional-Level Data for definitions of the group-level treatments, covariates and outcomes.
Section III. Empirical Strategy also defines the treament by expanded access to MWs.
Please refer to Section IV.B Individual-Level Data for definitions of the individual-level outcomes.
Appendix C in the Online Supplementary Material to the paper presents details about the individual-level data used in the paper.
In addition to information in section IV of the paper, more details on specific variables can be found in Lazuka, V. (2020) ‘Infant Health and Later-Life Labor Market Outcomes: Evidence from the Introduction of Sulpha Antibiotics in Sweden’, 
The Journal of Human Resources, vol. 55, no. 2, pp. 660–698.

The names of data variables used in the Replication Files:
1. Code_Paper:
id: a unique individual identifier
hospitalshare: hospital births per total live births X 100
earlymortality: 7-day mortality per 1000 live births
latemortality: 8-28-day mortality per 1000 live births
neonatalmortality: 28-day mortality per 1000 live births
lnlabourincome: the log of the real average real labor income between ages 47–64 (prior to the year of death or age 65 )
disabled: whether the individual received disability insurance on a permanent basis between ages 55–64
unemployed: whether the individual was unemployed at any time between ages 55–64
nonmanual: nonmanual occupation is a type of occupation of the individual aged between 34–49
service: service sector is a sector affiliation of the individual aged between 34–49
yearsofschooling: completed years of schooling
secondaryschool: secondary school completed
specificfield: obtained a specific field of education
totalhospitalstay: the total length of stay in hospital aged between 37–64
postXMW: a DD (groupXcohort) indicator whether the individual had access to the MW within 5.5 km (based on year of birth (the year of the MW opening) and municipality of birth)
pre(i)XMW: pre-treatment event-years, i=-1,-2,-3,-4,-5,<=-6 
post(i)XMW: post-treatment event-years, i=1,2,3,4,5,>=6 
postXTypeIMW: a DD (groupXcohort) indicator whether the individual had access to the Type I MW within 5.5 km (based on year of birth (the year of the MW opening) and municipality of birth)
postXTypeIIMW: a DD (groupXcohort) indicator whether the individual had access to the Type II MW within 5.5 km (based on year of birth (the year of the MW opening) and municipality of birth)
postXPrivateMW: a DD (groupXcohort) indicator whether the individual had access to the private MW within 5.5 km (based on year of birth (the year of the MW opening) and municipality of birth)
cointervention: a DD (groupXcohort) indicator of the cointervention
postXMWXCointervention: an intercation term between a DD indcator of the MW reform and a DD indicator of the cointervention 
sex: male/female
bmunicipality: municipality of birth
byear: year of birth
region_urban: regions defined by county-of-birth by the level-of-urbanization

2. Code_Appendix (additional variables):
premature: premature childbirth, per 1000 live births
stillbirths: stillbirths, per 1000 births
sickmothers: number of mothers who have a fever in 3 weeks after childbirth, per 1000
infectious: the total length of stay in hospital due to infectious/respiratory diseases aged between 37–64
cardiovascular: the total length of stay in hospital due to cardiovascular diseases aged between 37–64
diabetes: the total length of stay in hospital due to diabetes aged between 37–64
cancer: the total length of stay in hospital due to cancer aged between 37–64
degenerative: the total length of stay in hospital due to degenerative diseases aged between 37–64
mental: the total length of stay in hospital due to mental diseases aged between 37–64
other: the total length of stay in hospital due to other diseases aged between 37–64
postmortality: 29-365-day mortality, per 1000
childmortality: 1-14 ages mortality, per 1000
adultmortality1536: 15-36 ages mortality, per 1000
adultmortality3764: 37-64 ages mortality, per 1000
socialsciences: obtained a specific field of education - social sciences
naturalsciences: obtained a specific field of education - natural sciences
medicine: obtained a specific field of education - medicine
otherfields: obtained a specific field of education - other fields
agriculture: agriculture is a sector affiliation of the individual aged between 34–49
industry: industry and crafts is a sector affiliation of the individual aged between 34–49
building: building and construction is a sector affiliation of the individual aged between 34–49
transport: transport and communications is a sector affiliation of the individual aged between 34–49
publicservices: public services is a sector affiliation of the individual aged between 34–49
private: private services is a sector affiliation of the individual aged between 34–49
government: government is a sector affiliation of the individual aged between 34–49
publicadmin: public administration is a sector affiliation of the individual aged between 34–49
teaching: teaching and research is a sector affiliation of the individual aged between 34–49
lndoctors: ln doctors per 1000 mid-population
lnmidwives: ln midwives per 1000 mid-population
lnnurses: ln medical nurses per 1000 mid-population
lnhospitals: ln general hospitals per 1000 mid-population
lnexpenditures: ln real hospital expenditures (non-childbirth) per 1000 mid-population)
urban: urban municipality
north: municipality in the north
south: municipality in the south
lntraffic: ln trafficked road length per 1000
lnrailways: ln length of railways per 1000
lnmunincome: ln real municipal income per 1000
shareagriculture: share employed in agriculture
shareindustry: share employed in industry
countygdp: county gdp per capita
females: share females
under15: share under age 15
lncdr: ln crude death rate per 1000
sharedisabled: share disabled
lnschools: ln primary schools per 1000
lnbirths: ln live births
lnpharmacies: ln pharmacies per 1000
lnstillbirths: ln stillbirth rate per 1000 births
lnpop: ln mid-year population
lnimr: ln infant mortality rate per 1000 live births
lnmmr: ln maternal mortality rate per 1000
lnpneumonia: ln pneumonia mortality per 1000
sulpha: sulphonamides, grams per 1000
firstyearofMW: the first year since the bmunicipality has access to MW within 5.5 km radius
lbirths: live births per 1000 inhabitants
children: total children born to a mother
motherid: a unique identifier for the mother
motherschooling: mother's schoolingn (0=less than primary, 1=primary and more, 2=unknwown)
fatherses: father's SES (0=low 1=high 2=unknown)
fathersector: father's sector of employment (0=agriculture, 1=industry, 2=services, 3=unknown)
migrant: between-county migrant
distance: distance to the closest MW
lndistance: ln distance to the closest MW (0s were changed to 0.1 before creating it)
gravity: gravity-based access
originaldistance20: distance to the nearest MW is less than 20 km at the beginning of the reform
wrongregister_closest: the municipality of the closest MW is registering the birth instead of maternal parish of residence
mmunicipality: municipality of maternal residence

[C] All processing of individual data by the researcher takes place on servers located at Statistics Sweden via secure remote terminal access.
Stata v.16 was used. To speed up the computation process, BatchClient was available.
ArcGIS v.10.5 was used to construct minimal distances between the municipality centroids.

[X] How to access data used in this paper:
Indvidual-level data: The individual-level data (SIP) used in this paper are drawn from Swedish administrative registers and are confidential. 
However, this access is not unique and others can gain similar access by following a procedure described by Statistics Sweden https://www.scb.se/en/services/guidance-for-researchers-and-universities/. 
Researchers interested in obtaining this type of data could themselves apply for permission from the Swedish Ethical Review Board at https://etikprovningsmyndigheten.se/for-forskare/sa-gar-det-till/. 
Swedish Death Book was provided through the remote access at Lund University, but can be purchased at https://www.rotter.se/sw-death-index

Minicipality-level data: Statistics on population was purchased from Centre for Demographic and Ageing Research, Umeå University, at https://www.umu.se/en/centre-for-demographic-and-ageing-research/order-data/.
Information on hospital openings is taken from Skatteförvaltningen (1989) Sveriges Församlingar genom Tiderna, Stockholm, Graphic Systems.
Historical GIS maps were accessed from the Swedish National Archives, at https://riksarkivet.se/om.
Several archival sources from the Swedish National Archives were digitized with the financial help from Lund University, such as:
Riksarkivet (1930-1936) Rapport om Inspektion av Förlossnings- och Spädbarnshem 1930-1936, SE/RA/420177/14/F 13/2.
Riksarkivet (1931-1950) Medicinalstyrelsen Allmänna byrån, Lasarettsbyrån, Sjukhusbyrån, 1915-1967, SE/RA/420177/15.
Riksarkivet (1931-1946) Statistik Centralbyrån Födda, Vigda, Döda 1860–1947, https://sok.riksarkivet.se/scb-fodda-vigda-doda.
Riksarkivet (1938-1946) Årsberättelser från Mödra- och Barnavårdscentraler 1938-1966, SE/RA/420177/16/E 2 e.
Other sources were also digitized, such as:
Årsberättelser av Förste Provinsialläkaren 1931-1946, accessed at Lund University library, at https://www.lub.lu.se/sok/katalog-1957
Kommunala Financerna 1930, accessed at Lund University library, at https://www.lub.lu.se/sok/katalog-1957 
Other regional information comes from statistical yearbooks, freely downloadable from https://www.scb.se/hitta-statistik/aldre-statistik/innehall/serien-historisk-statistik-for-sverige/
These sources are listed in detail in Lazuka, V. (2020) ‘Infant Health and Later-Life Labor Market Outcomes: Evidence from the Introduction of Sulpha Antibiotics in Sweden’, 
The Journal of Human Resources, vol. 55, no. 2, pp. 660–698.





